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gnu: Add r-dsb.
* gnu/packages/bioconductor.scm (r-dsb): New variable. Change-Id: I34b91da1ae177bd37cfa548c5f6fede453f29bcd
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@ -5639,6 +5639,35 @@ (define-public r-dropletutils
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pseudo-cells, and downsampling of the count matrix.")
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pseudo-cells, and downsampling of the count matrix.")
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(license license:gpl3)))
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(license license:gpl3)))
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;; This is a CRAN package, but it depends on r-limma from Bioconductor.
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(define-public r-dsb
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(package
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(name "r-dsb")
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(version "1.0.3")
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(source
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(origin
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(method url-fetch)
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(uri (cran-uri "dsb" version))
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(sha256
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(base32 "1xzhd4q04c1vql49r6m4zskpx7f5hkl5hmdgr3gsbxb73xfs51v2"))))
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(properties `((upstream-name . "dsb")))
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(build-system r-build-system)
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(propagated-inputs (list r-limma r-magrittr r-mclust))
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(native-inputs (list r-knitr r-rmarkdown))
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(home-page "https://github.com/niaid/dsb")
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(synopsis
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"Normalize & denoise droplet single cell protein data (CITE-Seq)")
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(description
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"R-dsb improves protein expression analysis in droplet-based single-cell
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studies. The package specifically addresses noise in raw protein UMI counts
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from methods like CITE-seq. It identifies and removes two main sources of
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noise—protein-specific noise from unbound antibodies and droplet/cell-specific
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noise. The package is applicable to various methods, including CITE-seq,
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REAP-seq, ASAP-seq, TEA-seq, and Mission Bioplatform data. Check the vignette
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for tutorials on integrating dsb with Seurat and Bioconductor, and using dsb
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in Python.")
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(license license:cc0)))
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(define-public r-dss
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(define-public r-dss
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(package
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(package
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(name "r-dss")
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(name "r-dss")
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